Pith Number

pith:DIAXRENU

pith:2026:DIAXRENUE23EXZJJBKOJ7ULTR7

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Hyper-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control

Haoming Song, Huizhe Li, Jie Mei, Jinhao Zhang, Wenlong Xia, Yichen Lai, Youmin Gong, Zhexuan Zhou

Robot action trajectories are mostly low-frequency, so diffusion policies need only two denoising steps for strong performance.

arxiv:2605.01581 v4 · 2026-05-02 · cs.RO

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\usepackage{pith}
\pithnumber{DIAXRENUE23EXZJJBKOJ7ULTR7}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

across RoboTwin2.0, Adroit, MetaWorld, and real-world tasks, HDP3 achieves state-of-the-art performance with fewer than 1% of the parameters of prior 3D diffusion-based policies and substantially lower inference latency.

C2weakest assumption

That the low-frequency concentration observed in action trajectories and the derived error bound directly translate to sufficiency of exactly two denoising steps across the diverse tasks and action spaces tested, without hidden performance loss.

C3one line summary

Hydra-DP3 achieves SOTA visuomotor performance with under 1% of prior 3D diffusion policy parameters by using frequency analysis to justify a lightweight decoder and two-step DDIM inference.

Receipt and verification

First computed	2026-06-01T01:02:41.158164Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

1a017891b426b64be5290a9c9fd1738ff2900ecba55c18f5d1269e75af571e53

Aliases

arxiv: 2605.01581 · arxiv_version: 2605.01581v4 · doi: 10.48550/arxiv.2605.01581 · pith_short_12: DIAXRENUE23E · pith_short_16: DIAXRENUE23EXZJJ · pith_short_8: DIAXRENU

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/DIAXRENUE23EXZJJBKOJ7ULTR7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 1a017891b426b64be5290a9c9fd1738ff2900ecba55c18f5d1269e75af571e53

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0469e805ac3d77a3ba33a252121e21fdd7bc88b575caf1ae32d480e13d466ff3",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-02T19:07:09Z",
    "title_canon_sha256": "7a708af454819a9acd86f98df6920be10a4864f1e1c2dc8957e6aaa580104bea"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.01581",
    "kind": "arxiv",
    "version": 4
  }
}